基于粒子群算法的输变电施工网络优化研究
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摘要
本文分析了当前输变电施工进度网络图优化存在的主要问题和当前优化技术的发展趋势和现状。深入研究和分析了粒子群优化算法,根据算法的进化公式,提出了四种优化模型、并分析了其收敛特性以及算法早熟收敛的原因。针对算法的不足之处,提出了几点改进。针对输变电施工网络优化的特点,本文提出了基于粒子群优化算法的工期-费用优化模型、工期固定-资源均衡优化模型和资源受限-工期最短模型,并针对实际施工优化问题进行了计算仿真,仿真结果显示了算法应用于这一领域的可行性和有效性。本文通过对粒子群优化算法的深入研究,完善了算法的理论模型并进一步扩展了算法的应用领域,为工程施工优化问题提供了新的理论指导依据和高效的解决方案。
This Paper analyses the problems in the network optimization for transmit electricityengineering and the directions and status of the current optimization methods. Additionally,particle swarm optimization (PSO)algorithm has been studied and analyzed thoroughly.According to the evolutionary formulas of the algorithm, this paper proposes fouroptimization models and analyses the convergence characteristic and the reasons of prematureconvergence of the algorithm. In allusion to the specialties of the network optimization for thetransmit electricity engineering, this paper proposes the Time-cost optimization model andresource optimization model based on the particle swarm optimization algorithm. For solvingthese problems, numerical simulation results show the effectiveness and efficiency of usingPSO algorithm in this domain optimization. This paper provides a new theory directions andmethods for engineering optimization problems, based on the studies and researches on theparticle swarm optimization algorithm.
This Paper analyses the problems in the network optimization for transmit electricityengineering and the directions and status of the current optimization methods. Additionally,particle swarm optimization (PSO)algorithm has been studied and analyzed thoroughly.According to the evolutionary formulas of the algorithm, this paper proposes fouroptimization models and analyses the convergence characteristic and the reasons of prematureconvergence of the algorithm. In allusion to the specialties of the network optimization for thetransmit electricity engineering, this paper proposes the Time-cost optimization model andresource optimization model based on the particle swarm optimization algorithm. For solvingthese problems, numerical simulation results show the effectiveness and efficiency of usingPSO algorithm in this domain optimization. This paper provides a new theory directions andmethods for engineering optimization problems, based on the studies and researches on theparticle swarm optimization algorithm.
引文
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[7] Jinshing Yao and Fengtse Lin. Fuzzy Critical Path Method Based on Signed Distance Ranking of Fuzzy Numbers. IEEE TRANSACTIONS on Systems, Man and Cybernetics,Part A:Systems and Humans,2000,30(1):76～82
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[15] Yuan Hejin, Wang Cuiru, Zhang Jiangwei, Sun Chenjun. An Improved Particle Swarm Optimization Algorithm and its Application in Reactive Power Optimization of Power System. In: Progress in Intelligence Computation and Applications. Wuhan: China University of Geosciences Press,2005.446～453(ISTP 检索号:BCS66)
[16] Wang Cuiru, Zhang Jiangwei, Yang Jing etc. A Modified Particle Swarm Optimization Algorithm and its Application For Solving Traveling Salesman Problem.In:Proceedings 2005 International Conference on Neural Networks & Brain.Piscataway,NJ:IEEE Operations Center,2005. 689～694
[17] 王翠茹,黄志强,袁和金,张江维.基于改进粒子群优化和减聚类算法的 RBF 神经网络训练新方法. 计算机研究与发展,2005,42(9B):293～298
[18] Adedeji B.Badiru, P.Simin Pulat,项目管理原理,王瑜 译.北京:清华大学出版社,2003,107～160
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[20] 王诺.网络计划技术及其拓宽研究.北京:冶金工业出版社,1999,31～40
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[22] Wolpert D H,Macteady W G. No Free Lunch for Optimization. IEEE Transaction on Evolutionary Computation, 1997,1(1):67～82
[23] 丁永生.计算智能-理论、技术与应用.北京:科学出版社,2004,3～8
[24] 王正志,薄涛.进化计算.长沙:国防科技大学出版社,2000,12～30
[25] J.C. Bezdek, On the relationship between neural networks, pattern recognition and intelligence, Int. J. Approximate Reasoning, 1992,6, 85～107
[26] 潘峰.计算智能研究与应用:[博士学位论文].北京:北京理工大学信息科学技术学院自动控制系,2004
[27] 徐宗本, 张讲社,等.计算智能中的仿生学.科学出版社,2003,25～36
[28] Holland J H. Adaptation in Natural and Artificial Systems. The University of Michigan Press,1975
[29] Fogel L J, Owens AJ, Walsh M J. Artificial Intelligence through Simulated Evolution. John Wiley, New York,1966
[30] Koza J R. Genetic Programming: On the Programming of Computers by Means of Natural Selection. MIT Press, Cambridge,1992
[31] Clerc M. The Swarm and the Queen: Towards a Deterministic and Adaptive Particle Swarm Optimization. In: Proc. 1999 Congress on Evolutionary Computation. Washington, DC, Piscataway, NJ:IEEE Service Center, 1999.1951～1957
[32] Jie Chen, Feng Pan, Tao Cai, etc. The Stability Analysis of Particle Swarm Optimization Condition Constrain,Journal of Control Theory and Applications,2004,1(1):86～90
[33] Kennedy.J, Mendes R. Population structure and particle swarm performance. In: Proceedings of the 2002 Congress on Evolutionary Computation,2002,(2):1671～1676
[34] Kennedy J, Eberhart R C. A Discrete Binary Version of the Particle Swarm Algorithm. In: Proceedings 1997 Conf. On Systems, Man and Cybernetics. Piscataway, NJ: IEEE Service Center,1997,4104～4109
[35] Lovbjerg M, Rasmussen T.K, Krink T. Hybrid Particle Swarm Optimiser with Breeding and Subpopulations. In: Proceedings of the Genetic and Evolutionary Computation Conference,2001
[36] Parsopoulos K.E, Plagianakos V. P, Magoulas G.D, etc. Improving particle swarm optimizer by function "stretching", Advances in Convex Analysis and Global Optimization,2001.445～457
[37] 潘峰,涂序彦,陈杰,付继伟.协调粒子群优化算法—HPSO.计算机工程,2005,31(1):169～171
[38] Parsopoulos, K. E. and Vrahatis, M. N. Particle swarm optimization method in multiobjective problems. In: Proceedings of the ACM Symposium on Applied Computing,2002.603～607
[39] 侯志荣,吕振肃,IIR 数字滤波器设计的粒子群优化算法.电路与系统学报, 2003,8(4):16～20
[40] 龙云,王建全.基于粒子群游算法的同步发电机参数辨识.大电机技术, 2003,32(1):8～11
[41] 夏永明,付子义,袁世鹰,程志平.粒子群优化算法在直线感应电机优化设计中的应用.中小型电机, 2002,29(6):14～16
[42] Yoshida H, Kawata K, Fukuyama Y, et al. A Particle Swarm Optimization for Reactive Power and Voltage Control Considering voltage Stability. In: Proc. Intl. Conf. on Intelligent System Application to Power Systems, Rio de Janeiro, Brazil, 1999.117～121
[43] Fukuyama Y, Yoshida H. A Particle Swarm Optimization for Reactive Power and Voltage Control in Electric Power Systems. In: Proc. Congress on Evolutionary Computation 2001. Seoul, Korea. Piscataway, NJ:IEEE Service Center,2001.87～93
[44] Shi,Y,Eberhart,R.C, Parameter selection in particle swarm optimization, Evolutionary Programming VII: Proceedings of the Seventh Annual Conference on Evolutionary Programming,New York,1998.591～600
[45] M.Clerc, J.Kennedy, The particle swarm: explosion stability and convergence in a multi-dimensional complex space, IEEE Trans. Evolution. Comput,2002,(6):58～73
[46] 李兵,蒋慰孙.混沌优化方法及其应用.控制理论与应用,1997,14(4):613～615
[47] 王战权,赵朝义,云庆夏.进化策略中基于柯西分布的变异算子改进探讨.系统工程,1999,17(4):49～54
[48] 李万庆,王文鹏,李文华,卫赵斌.基于遗传算法的网络计划工期-费用优化.建筑技术开发,2002,29(4):51～53
[2] Shipeng Luo, Cheng Wang, Jinwen Wang. Ant Colony Optimization for Resource-Constrained Project Scheduling With Generalized Precedence. In: 15th IEEE International Conference on Tools with Artificial Intelligence,2003.284～289
[3] Khalil S.Hindi, Hongbo Yang, Krzysztof Fleszar. An Evolutionary Algorithm for Resource-Constrained Project Scheduling. IEEE Transactions On Evolutionary Computation,2002,6(5):512～518
[4] Len, S, Hung,T. A Genetic Algorithm based Optimal resource-constrained scheduling simulatin model. Construction Management and Economics,2002,20(2):131～141
[5] 田军,寇纪松,李敏强.利用遗传算法优化施工网络计划.系统工程理论与实践, 1999,19(5):78～82
[6] 董鸣皋,刘发全.基于 MS-Project2000VBA 技术的网络资源优化计算机模型设计.系统工程理论与实践,2003,23(12):133～137
[7] Jinshing Yao and Fengtse Lin. Fuzzy Critical Path Method Based on Signed Distance Ranking of Fuzzy Numbers. IEEE TRANSACTIONS on Systems, Man and Cybernetics,Part A:Systems and Humans,2000,30(1):76～82
[8] 姚玉玲.网络计划资源均衡优化方法的研究.西安矿业学报,1998,18(1):45～49,54
[9] 王凌.智能优化算法及其应用.北京:清华大学出版社,2001,36～59
[10] 丁建立,陈增强,袁著祉.智能仿生算法及其网络优化中的应用研究进展.计算机工程与应用,2003,39(12):10～14
[11] Kennedy J, Eberhart R C, Shi Y. Swarm Intelligence. Sanfrancisco: Morgan Kaufman Publisher,2001:12～36
[12] Dorigo.M, Maniezzo V, Colorni A. The ant system: Optimization by a colony of cooperating agents. IEEE Transactions on Systems Man and Cybernetics,Part B,1996,26(1):29～41
[13] Kennedy J, Eberhart R C. Particle swarm optimization.In: Proc. IEEE Int. Conf. Neural Networks. Piscataway, NJ:IEEE Press,1995.1942～1948
[14] Shi.Y,Eberhart R. A modified particle swarm opt-imizer In:IEEE World Congress on Computational Intelligence,1998.69～73
[15] Yuan Hejin, Wang Cuiru, Zhang Jiangwei, Sun Chenjun. An Improved Particle Swarm Optimization Algorithm and its Application in Reactive Power Optimization of Power System. In: Progress in Intelligence Computation and Applications. Wuhan: China University of Geosciences Press,2005.446～453(ISTP 检索号:BCS66)
[16] Wang Cuiru, Zhang Jiangwei, Yang Jing etc. A Modified Particle Swarm Optimization Algorithm and its Application For Solving Traveling Salesman Problem.In:Proceedings 2005 International Conference on Neural Networks & Brain.Piscataway,NJ:IEEE Operations Center,2005. 689～694
[17] 王翠茹,黄志强,袁和金,张江维.基于改进粒子群优化和减聚类算法的 RBF 神经网络训练新方法. 计算机研究与发展,2005,42(9B):293～298
[18] Adedeji B.Badiru, P.Simin Pulat,项目管理原理,王瑜 译.北京:清华大学出版社,2003,107～160
[19] 夏平生.关键路径法与计划评审法.北京:电力工业出版社,1981,1～30
[20] 王诺.网络计划技术及其拓宽研究.北京:冶金工业出版社,1999,31～40
[21] 曾建潮,介婧,崔志华.微粒群算法.北京:科学出版社,2004,1～50
[22] Wolpert D H,Macteady W G. No Free Lunch for Optimization. IEEE Transaction on Evolutionary Computation, 1997,1(1):67～82
[23] 丁永生.计算智能-理论、技术与应用.北京:科学出版社,2004,3～8
[24] 王正志,薄涛.进化计算.长沙:国防科技大学出版社,2000,12～30
[25] J.C. Bezdek, On the relationship between neural networks, pattern recognition and intelligence, Int. J. Approximate Reasoning, 1992,6, 85～107
[26] 潘峰.计算智能研究与应用:[博士学位论文].北京:北京理工大学信息科学技术学院自动控制系,2004
[27] 徐宗本, 张讲社,等.计算智能中的仿生学.科学出版社,2003,25～36
[28] Holland J H. Adaptation in Natural and Artificial Systems. The University of Michigan Press,1975
[29] Fogel L J, Owens AJ, Walsh M J. Artificial Intelligence through Simulated Evolution. John Wiley, New York,1966
[30] Koza J R. Genetic Programming: On the Programming of Computers by Means of Natural Selection. MIT Press, Cambridge,1992
[31] Clerc M. The Swarm and the Queen: Towards a Deterministic and Adaptive Particle Swarm Optimization. In: Proc. 1999 Congress on Evolutionary Computation. Washington, DC, Piscataway, NJ:IEEE Service Center, 1999.1951～1957
[32] Jie Chen, Feng Pan, Tao Cai, etc. The Stability Analysis of Particle Swarm Optimization Condition Constrain,Journal of Control Theory and Applications,2004,1(1):86～90
[33] Kennedy.J, Mendes R. Population structure and particle swarm performance. In: Proceedings of the 2002 Congress on Evolutionary Computation,2002,(2):1671～1676
[34] Kennedy J, Eberhart R C. A Discrete Binary Version of the Particle Swarm Algorithm. In: Proceedings 1997 Conf. On Systems, Man and Cybernetics. Piscataway, NJ: IEEE Service Center,1997,4104～4109
[35] Lovbjerg M, Rasmussen T.K, Krink T. Hybrid Particle Swarm Optimiser with Breeding and Subpopulations. In: Proceedings of the Genetic and Evolutionary Computation Conference,2001
[36] Parsopoulos K.E, Plagianakos V. P, Magoulas G.D, etc. Improving particle swarm optimizer by function "stretching", Advances in Convex Analysis and Global Optimization,2001.445～457
[37] 潘峰,涂序彦,陈杰,付继伟.协调粒子群优化算法—HPSO.计算机工程,2005,31(1):169～171
[38] Parsopoulos, K. E. and Vrahatis, M. N. Particle swarm optimization method in multiobjective problems. In: Proceedings of the ACM Symposium on Applied Computing,2002.603～607
[39] 侯志荣,吕振肃,IIR 数字滤波器设计的粒子群优化算法.电路与系统学报, 2003,8(4):16～20
[40] 龙云,王建全.基于粒子群游算法的同步发电机参数辨识.大电机技术, 2003,32(1):8～11
[41] 夏永明,付子义,袁世鹰,程志平.粒子群优化算法在直线感应电机优化设计中的应用.中小型电机, 2002,29(6):14～16
[42] Yoshida H, Kawata K, Fukuyama Y, et al. A Particle Swarm Optimization for Reactive Power and Voltage Control Considering voltage Stability. In: Proc. Intl. Conf. on Intelligent System Application to Power Systems, Rio de Janeiro, Brazil, 1999.117～121
[43] Fukuyama Y, Yoshida H. A Particle Swarm Optimization for Reactive Power and Voltage Control in Electric Power Systems. In: Proc. Congress on Evolutionary Computation 2001. Seoul, Korea. Piscataway, NJ:IEEE Service Center,2001.87～93
[44] Shi,Y,Eberhart,R.C, Parameter selection in particle swarm optimization, Evolutionary Programming VII: Proceedings of the Seventh Annual Conference on Evolutionary Programming,New York,1998.591～600
[45] M.Clerc, J.Kennedy, The particle swarm: explosion stability and convergence in a multi-dimensional complex space, IEEE Trans. Evolution. Comput,2002,(6):58～73
[46] 李兵,蒋慰孙.混沌优化方法及其应用.控制理论与应用,1997,14(4):613～615
[47] 王战权,赵朝义,云庆夏.进化策略中基于柯西分布的变异算子改进探讨.系统工程,1999,17(4):49～54
[48] 李万庆,王文鹏,李文华,卫赵斌.基于遗传算法的网络计划工期-费用优化.建筑技术开发,2002,29(4):51～53